Abstract
ABSTRACTThe present research analyses the power consumption (Pc) and surface roughness (Ra) in hard turning of high‐strength low‐alloy (HSLA) grade AISI 4140 steel using a recently developed AlTiSiN‐coated carbide tool under different cooling‐lubrication conditions (dry, flooded, nanofluid‐MQL). The nanofluid was prepared by mixing the MWCNT nanoparticles with an eco‐friendly automotive radiator coolant (base fluid). The cooling‐lubrication performance is investigated briefly by comparing the machining responses like machined surface morphology, tool wear, cutting force and temperature. The experiments associated with 46 trials were performed by considering various machining variables, namely cutting speed, nose radius, depth of cut, feed and cooling‐lubrication methods. From the perspective of predictive modelling and multi‐response optimisation, response surface methodology has been employed to minimise power consumption and surface roughness. Thereafter, the predictive modelling and optimisation results are implemented for economic analysis and energy‐saving carbon footprint evaluation. This innovative research also addresses comparative environmental sustainability evaluation in hard turning under different cooling‐lubrication conditions using a life cycle assessment methodology for cleaner and safer production. Results indicate that cutting speed was the most influential item in power consumption enhancement. Furthermore, compared with dry and flooded turning, lower cutting force, reduced cutting temperature, shorter width of flank wear and better surface morphology were obtained under nanofluid‐MQL machining. It has been observed that nanofluid‐MQL machining outperformed sustainability improvement concerning techno‐economically viable societal acceptable and environmental friendliness.
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